Modelling and Simulation in Engineering / 2013 / Article / Tab 2

Research Article

Prediction of Surface Roughness When End Milling Ti6Al4V Alloy Using Adaptive Neurofuzzy Inference System

Table 2

Experimental results used in training phase.

No.Cutting speed (m/min)Feed rate (mm/rev)Depth of cut (mm)Surface roughness (µm)
PVD Uncoated

177.50.110.550.55
21050.11.50.350.666
377.50.151.50.90.783
477.50.151.50.860.85
5500.1510.720.565
677.50.211.321.426
71050.1520.80.767
81050.21.51.321.912
9500.1520.71.173
101050.1510.580.84
1177.50.151.50.90.673
12500.21.50.81.444
1377.50.220.911.66
1477.50.121.320.856

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